[PDE CERTIFICATE - EXAMTOPIC] DUMPS Q96-Q100

Google Professional Data Engineer Certificate EXAMTOPIC DUMPS Q96-Q100

Q 96.

You want to analyze hundreds of thousands of social media posts daily at the lowest cost and with the fewest steps. You have the following requirements:

• You will batch-load the posts once per day and run them through the Cloud Natural Language API.
• You will extract topics and sentiment from the posts.
• You must store the raw posts for archiving and reprocessing.
• You will create dashboards to be shared with people both inside and outside your organization.
  You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?

• ❌ A. Store the social media posts and the data extracted from the API in BigQuery.
• ❌ B. Store the social media posts and the data extracted from the API in Cloud SQL.
• ⭕ C. Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.
• ❌ D. Feed to social media posts into the API directly from the source, and write the extracted data from the API into BigQuery.
  → Must store the raw posts

Integrated repository for analytics and ML

• Media content storage Cloud Storage
• Analysis / Dashboards BigQuery

Q 97.

You store historic data in Cloud Storage. You need to perform analytics on the historic data. You want to use a solution to detect invalid data entries and perform data transformations that will not require programming or knowledge of SQL. What should you do?

• ❌ A. Use Cloud Dataflow with Beam to detect errors and perform transformations.
• ⭕ B. Use Cloud Dataprep with recipes to detect errors and perform transformations.
• ❌ C. Use Cloud Dataproc with a Hadoop job to detect errors and perform transformations.
• ❌ D. Use federated tables in BigQuery with queries to detect errors and perform transformations.

Cloud Dataprep

Dataprep

ETL processes on GCP for low/no-code solutions : Data Fusion & Cloud Dataprep

Dataprep

• More refined and cost-effective but limited in capability
• Third-party application : Managed _Trifacta for preparing and analysing quality and transforming the input data
• Service for visually exploring, cleaning, and preparing data for analysis.
• Can transform data of any size stored in CSV, JSON, or relational table formats